The human eye reacts to light in different ways based on the response of rods and cones in the retina. Specifically, the perception of the response of the eye is different for different colors (e.g., red, green, and blue) in the visible spectrum as well as between luminance and chrominance. Conventional techniques for capturing digital images rely on a CMOS image sensor or CCD image sensor positioned under a color filter array such as a Bayer color filter. Each photodiode of the image sensor samples an analog value that represents an amount of light associated with a particular color at that pixel location. The information for three or more different color channels may then be combined (or filtered) to generate a digital image.
The resulting images generated by these techniques have a reduced spatial resolution due to the blending of values generated at different discrete locations of the image sensor into a single pixel value in the resulting image. Fine details in the scene could be represented poorly due to this filtering of the raw data.
Furthermore, based on human physiology, it is known that human vision is more sensitive to luminance information than chrominance information. In other words, the human eye can recognize smaller details due to changes in luminance when compared to changes in chrominance. However, conventional image capturing techniques do not typically exploit the differences in perception between chrominance and luminance information. Thus, there is a need to address these issues and/or other issues associated with the prior art.